Khlood M. Mehdar¹, Toufique A. Soomro^2,3,*, Ahmed Ali⁴, Faisal Bin Ubaid⁵, Muhammad Irfan^6,*, Sabah Elshafie Mohammed Elshafie¹, Aisha M. Mashraqi⁷, Abdullah A. Asiri⁸, Nagla Hussien Mohamed Khalid⁸, Hanan T. Halawani⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3091-3132, 2025, DOI:10.32604/cmes.2025.065471 - 30 June 2025

Abstract Breast cancer remains one of the most pressing global health concerns, and early detection plays a crucial role in improving survival rates. Integrating digital mammography with computational techniques and advanced image processing has significantly enhanced the ability to identify abnormalities. However, existing methodologies face persistent challenges, including low image contrast, noise interference, and inaccuracies in segmenting regions of interest. To address these limitations, this study introduces a novel computational framework for analyzing mammographic images, evaluated using the Mammographic Image Analysis Society (MIAS) dataset comprising 322 samples. The proposed methodology follows a structured three-stage approach. Initially,… More >

Jagadesh Balasubramani¹, Surendran Rajendran^1,*, Mohammad Zakariah², Abeer Alnuaim²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2793-2807, 2025, DOI:10.32604/cmc.2025.062266 - 16 April 2025

Abstract Autism spectrum disorder (ASD) is a multifaceted neurological developmental condition that manifests in several ways. Nearly all autistic children remain undiagnosed before the age of three. Developmental problems affecting face features are often associated with fundamental brain disorders. The facial evolution of newborns with ASD is quite different from that of typically developing children. Early recognition is very significant to aid families and parents in superstition and denial. Distinguishing facial features from typically developing children is an evident manner to detect children analyzed with ASD. Presently, artificial intelligence (AI) significantly contributes to the emerging computer-aided… More >

Chunlai Du^1,#, Xin Gu^1,#, Yanhui Guo^2,*, Siqi Guo³, Ziwei Pang³, Yi Du³, Guoqing Du^3,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3435-3450, 2025, DOI:10.32604/cmc.2025.060212 - 16 April 2025

Abstract Coronary artery disease is a highly lethal cardiovascular condition, making early diagnosis crucial for patients. Echocardiograph is employed to identify coronary heart disease (CHD). However, due to issues such as fuzzy object boundaries, complex tissue structures, and motion artifacts in ultrasound images, it is challenging to detect CHD accurately. This paper proposes an improved Transformer model based on the Feedback Self-Attention Mechanism (FSAM) for classification of ultrasound images. The model enhances attention weights, making it easier to capture complex features. Experimental results show that the proposed method achieves high levels of accuracy, recall, precision, F1 More >

Khushmeen Kaur Brar¹, Bhawna Goyal¹, Ayush Dogra², Sampangi Rama Reddy³, Ahmed Alkhayyat⁴, Rajesh Singh⁵, Manob Jyoti Saikia^6,7,*

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4217-4263, 2024, DOI:10.32604/cmc.2024.052548 - 19 December 2024

Abstract Skin cancer has been recognized as one of the most lethal and complex types of cancer for over a decade. The diagnosis of skin cancer is of paramount importance, yet the process is intricate and challenging. The analysis and modeling of human skin pose significant difficulties due to its asymmetrical nature, the visibility of dense hair, and the presence of various substitute characteristics. The texture of the epidermis is notably different from that of normal skin, and these differences are often evident in cases of unhealthy skin. As a consequence, the development of an effective… More >

Cheng Wan¹, Jiani Zhao¹, Xiangqian Hong², Weihua Yang^2,*, Shaochong Zhang^2,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 391-407, 2024, DOI:10.32604/cmc.2024.048307 - 25 April 2024

Abstract Age-related macular degeneration (AMD) ranks third among the most common causes of blindness. As the most conventional and direct method for identifying AMD, color fundus photography has become prominent owing to its consistency, ease of use, and good quality in extensive clinical practice. In this study, a convolutional neural network (CSPDarknet53) was combined with a transformer to construct a new hybrid model, HCSP-Net. This hybrid model was employed to tri-classify color fundus photography into the normal macula (NM), dry macular degeneration (DMD), and wet macular degeneration (WMD) based on clinical classification manifestations, thus identifying and… More >

Huan Wang¹, Shi Qiu^1,2,*, Benyue Zhang¹, Lixuan Xiao³

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1569-1589, 2024, DOI:10.32604/cmc.2023.046821 - 27 February 2024

Abstract Lung cancer is a malady of the lungs that gravely jeopardizes human health. Therefore, early detection and treatment are paramount for the preservation of human life. Lung computed tomography (CT) image sequences can explicitly delineate the pathological condition of the lungs. To meet the imperative for accurate diagnosis by physicians, expeditious segmentation of the region harboring lung cancer is of utmost significance. We utilize computer-aided methods to emulate the diagnostic process in which physicians concentrate on lung cancer in a sequential manner, erect an interpretable model, and attain segmentation of lung cancer. The specific advancements… More >

Kun Yang^1,2,3, Shilong Chang¹, Yucheng Wang¹, Minghui Wang¹, Jiahui Yang¹, Shuang Liu^1,2,3, Kun Liu^1,2,3, Linyan Xue^1,2,3,*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 393-410, 2024, DOI:10.32604/cmc.2023.044994 - 30 January 2024

Abstract Clear cell renal cell carcinoma (ccRCC) represents the most frequent form of renal cell carcinoma (RCC), and accurate International Society of Urological Pathology (ISUP) grading is crucial for prognosis and treatment selection. This study presents a new deep network called Multi-scale Fusion Network (MsfNet), which aims to enhance the automatic ISUP grade of ccRCC with digital histopathology pathology images. The MsfNet overcomes the limitations of traditional ResNet50 by multi-scale information fusion and dynamic allocation of channel quantity. The model was trained and tested using 90 Hematoxylin and Eosin (H&E) stained whole slide images (WSIs), which… More >

Hassen Louati^1,2, Ali Louati^3,*, Elham Kariri³, Slim Bechikh²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2519-2547, 2024, DOI:10.32604/cmes.2023.030806 - 15 December 2023

Abstract Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues, particularly in the field of lung disease diagnosis. One promising avenue involves the use of chest X-Rays, which are commonly utilized in radiology. To fully exploit their potential, researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems. However, constructing and compressing these systems presents a significant challenge, as it relies heavily on the expertise of data scientists. To tackle this issue, we propose an automated approach that utilizes an evolutionary algorithm (EA) to optimize the design and compression More >

Fayaz Muhammad¹, Jahangir Khan¹, Asad Ullah¹, Fasee Ullah¹, Razaullah Khan², Inayat Khan², Mohammed ElAffendi³, Gauhar Ali^3,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 647-664, 2023, DOI:10.32604/cmc.2023.038748 - 31 October 2023

Abstract IIF (Indirect Immune Florescence) has gained much attention recently due to its importance in medical sciences. The primary purpose of this work is to highlight a step-by-step methodology for detecting autoimmune diseases. The use of IIF for detecting autoimmune diseases is widespread in different medical areas. Nearly 80 different types of autoimmune diseases have existed in various body parts. The IIF has been used for image classification in both ways, manually and by using the Computer-Aided Detection (CAD) system. The data scientists conducted various research works using an automatic CAD system with low accuracy. The… More >

Mohammed Jasim Mohammed Jasim¹, Bzar Khidir Hussan², Subhi R. M. Zeebaree^3,*, Zainab Salih Ageed⁴

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3677-3693, 2023, DOI:10.32604/cmc.2023.037363 - 31 March 2023

Abstract The major mortality factor relevant to the intestinal tract is the growth of tumorous cells (polyps) in various parts. More specifically, colonic polyps have a high rate and are recognized as a precursor of colon cancer growth. Endoscopy is the conventional technique for detecting colon polyps, and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss rate. The automated diagnosis of polyps in a computer-aided diagnosis (CAD) method is implemented using statistical analysis. Nowadays, Deep Learning,… More >